04/21/23 | pag. 1

A comprehensive health impact assessment framework for traffic in Flanders and Brussels

Dhondt, S., Macharis, C. & Putman, K.

HIA 2011 - Granada

Background

• Impact of transport on health• Air pollution, noise, traffic accidents, impact on

physical health or psychological consequences

• Significant challenge to policy in Belgium

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• Number of traffic victims still higher than neighbouring countries

• European Commission takes Belgiumto EU Court of Justice for failing to comply with EU air quality limit values for PM10.

HIA for evaluating policy

Need for more integrated, systemic policy responses

HIA to evaluate the health burden of policy responsesMASE: “Model-based Approach for evaluating the Safety and Environmental effect of traffic policy measures”

• Model based– Alignment of different models to assess population exposure

• Safety and Environment– Impact of air pollution and traffic safety expressed in DALY

• Traffic policy measures– E.g. teleworking, ageing population, more efficient public

transport and increasing fuel prices

HIA framework for traffic policy04/21/23 | pag. 3

The MASE-project is funded by the Flemish agency for Innovation by Science and Technology

Model-Based Approach

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Transport model

Road safety model

Health Impact Assessment

Emission and dispersion model

Health impact of air pollution

– Selection of exposures and health endpoints• Years Life Lost (YLL)

– PM2,5: long term mortality

– O3: long-term mortality (summer period only)

• Years Lived with Disability (YLD)– PM10: cause – specific hospital admissions (short –term)

– Population exposure• Dynamic exposure: incorporating spatial and

temporal variability of population and pollution

– Exposure-effect evaluation• Established and recent RR from epidemiology

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Health impact of air pollution

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Dynamic exposure

Dynamic exposure

Titel van de presentatie04/21/23 | pag. 7

a)

d)

b)

e)

c)

f)

Ambient PM2.5

concentrations at 02h and 14h

Population density at a random day both at 02h and 14h

Dynamic exposure

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Relative difference in PM2.5 exposure using a static vs a dynamic exposure assessment

Health impact of air pollution

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Age Sex

PM2,5

ICD10 I00-I70 J00-J99O3 (summer)

ICD10 J00-J99 Attributable proportion of

PM2,5 and O3 to total YLL

Exposure µg/m3

YLL/1000 [95% CI]

Exposure µg/m3

YLL/1000[95% CI]

34-54Male 18,63 2,15

[1,51 – 2,79] 77,99 0,11[0,04 – 0,18]

16,12%[11,04 – 21,19%]

Female 18,56 1,17[0,82 - 1,52] 78,17 0,08

[0,03 – 0,14]16,10%

[11,02 – 21,18%]

55-64Male 18,61 8,88

[6,23 – 11,52] 78,27 0,72[0,28 – 1,17]

16,46%[11,17 – 21,74%]

Female 18,58 4,30[3,02 – 5,58] 78,27 0,41

[0,16 – 0,69]16,68%

[11,25 – 22,11%]

>=65Male 18,64 26,02

[18,27 – 33,76] 78,18 3,07[1,19 – 4,96]

17,10%[11,43 – 22,77%]

Female 18,67 20,98[14,74 – 27,22] 78,09 1,82

[0,70 – 2,94]16,64%

[11,26 – 22,03%]

Total 8,14 [5,81 – 10,74]

0,78 [0,30 – 1,27]

16,56%[11,21 – 21,90%]

YLL due to PM2.5 and O3 (base-scenario)

Health impact of traffic safety

– Selection of exposures and health endpoints• Public health impact of injured and fatal traffic

victims– YLL: number of fatal traffic victims– YLD: burden of injury

– Population exposure• Based on traffic risk models

– Number of fatal and hospitalized traffic victims under changing mobility patterns

– Exposure-effect evaluation• Injury risks derived from hospital registration (ICD-

9-CM)

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Health impact of traffic safety

Probabilistic model– Monte Carlo analysis

• Parameters– Injury risk

– Risk of lifelong or temporary disability

– Disability weights

– Life expectancy

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Health impact of traffic safety

DALY due to road traffic accidents (base-scenario)

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Age Sex Nr DALY [95% CI] Average DALY(/1000)

Average DALY per kilometer

18-34Male 1508 13376,96 [12441 – 14388] 14,048 948,74

Female 524 2271,59 [1851 – 2769] 2,423 213,11

35-54Male 1085 5578,08 [4994 – 6245] 5,435 271,29

Female 466 1671,47 [1341 – 2092] 1,663 123,42

55-64Male 280 1215,42 [1047 – 1434] 3,510 173,98

Female 153 432,38 [352 – 558] 1,184 102,53

≥ 65Male 385 939,24 [770 – 1143] 2,537 212,13

Female 374 637,46 [490 – 819] 1,173 202,59

Total 4775 26122,60 [25634 – 33224] 4,710 336,46

Integration

Comparison health burden (base-scenario)

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Age SexAverage DALY

(/1000)TRAFFIC SAFETY

Average DALY(/1000)

AIR POLLUTION

35-54Male 5,435 2,273

Female 1,663 1,256

55-64Male 3,510 9,604

Female 1,184 4,716

≥ 65Male 2,537 29,098

Female 1,173 22,806Total 4,710 9,066

Next steps

• Enhanced population exposure– Simulating individual people throughout the

day• More detailed exposure profile

– Exposure of children• School locations

• Follow-up on epidemiologic studies– Relative risks derived from dynamic exposure

instead of residential exposure

• Scenario analysesHIA framework for traffic policy04/21/23 | pag. 14

HIA framework for traffic policy04/21/23 | pag. 15

Thank you for your attention!

stijn.dhondt@vub.ac.be